How Intelligent Traffic Management Makes Smarter Use of Transport Possible?

AI-based approaches have now allowed authorities to move to the next stage by helping them detect other violations that were not previously possible on the same infrastructure.

Fremont, CA: Over the past decade, rapid developments in the fields of optics (camera), processing and networking have made a significant contribution to transforming the security and surveillance industry landscape (including traffic enforcement and management). Thanks to advanced software and hardware technologies, it allows law enforcement agencies by improving their capabilities in a real-time and cost-effective way, not just for enforcement (detecting violations) but overall traffic management and observations software suite of ITMS leverages advanced Artificial Intelligence and Machine Learning techniques that add a smart layer to standard IP cameras. This makes it possible to detect several forms of infringement and help generate warnings for the same. The data visualization layer allows traffic authorities to consider city-wide ground conditions and patterns, helping traffic authorities prepare and take pre-emptive steps.

The brains of the scheme are robust deep learning algorithms, video processing, and edge-AI hardware. These capabilities enable both the capture of events as they occur and the analysis of critical insights and efficient resource planning to be extracted.

Today, the city and the authorities need a new approach that can be adapted to their needs for traffic management. This means finding the issue and a remedy that allows the authorities to see a thorough analysis before infringements are distributed within the ticket generation system. The good news is that it brings cost-effective, city-wide traffic law enforcement within reach by incorporating innovations like computer vision and artificial intelligence (AI).

It can be tricky to achieve absolute traffic control solely based on human efforts. However, in different cities, AI and ML solutions have largely helped solve traffic problems. AI algorithms cut long processes and aid in a fraction of seconds to evaluate the reported data and numbers effectively while minimizing the chance of errors. Traffic control and compliance have become highly scalable and efficient with the right processors and other technologies.

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